MRI Biomarkers of Patients with Tuberous Sclerosis Complex and Autism Tuberous sclerosis complex (TSC) is an autosomal dominant disease characterized by the presence of benign tumors, called hamartomas, which can affect virtually every organ system of the body, including the brain. The prognosis for individuals with TSC varies in accordance with the severity of the specific symptoms. While severe manifestations may be seen in individuals diagnosed in childhood, mild forms of the disease may be observed in men and women diagnosed in adulthood. The cause of neurological deficits in TSC patients is a key unresolved question. Our key hypothesis is that the development of autistic spectrum disorders (ASD) in TSC patients is a consequence of abnormal white matter development and maturation. This hypothesis is supported by both animal model findings of axonal miswiring and hypomyelination, and studies with TSC patients using diffusion imaging that have identified brain structural changes consistent with aberrant connectivity and loss of myelination. These suggest that adverse cognitive/social/behavioral outcomes may be due to alterations in white matter connectivity and microstructural integrity, not the cortical tubers that are the most obviou brain abnormalities in TSC. TSC is a genetic disorder with a well understood genetic basis for abnormal brain development, for which brain modifying drug therapy is currently available. The ability to characterize brain abnormalities in TSC with and without ASD will be crucial to the development of a drug therapy for ASD in TSC. Our overall objective is to identify the brain changes that are associated with ASD in patients with TSC, by the evaluation of advanced MRI of healthy controls, ASD patients without TSC, and TSC patients with and without ASD. We propose to recruit a cohort of children, aged 5-10 years old, and to carry out comprehensive MRI, image analysis and cognitive phenotyping. We propose to study these children longitudinally for five years. We propose to develop and evaluate a set of quantitative anatomic and diffusion MRI measures that characterize white matter, cortical and subcortical gray matter, and harmatomas. In order to improve the accuracy and reliability of the MRI measures, we will develop novel algorithms for MRI analysis of these subjects building on our own recent work, implement open source software tools to apply these algorithms, and validate these tools in comparison to conventional analysis strategies. We will distribute the imaging data and these software tools to the imaging community. The primary outcome will be the development for the first time of a capability discriminate between controls, patients with ASD without TSC, TSC patients without ASD and TSC patients with ASD.